Goce Dimitrov

University of Bristol | UB · Department of Computer Science

The video technology scenery has been very vivid over the past years, with novel video coding technologies introduced that promise improved compression performance over state-of-the-art technologies. Despite the fact that a lot of video datasets are available, representative content of the wide parameter space along with subjective evaluations of v...

In this paper, the performance of three state-of-the-art video codecs: High Efficiency Video Coding (HEVC) Test Model (HM), AOMedia Video 1 (AV1) and Versatile Video Coding Test Model (VTM), are evaluated using both objective and subjective quality assessments. Nine source sequences were carefully selected to offer both diversity and representative...

Highly textured video content is challenging to compress since the bit-rate to video quality trade-off is high and complex perceptual masking influences performance. Test datasets that cover a wide range of texture types are thus important for codec evaluation, but few exist. In order to study the properties of video texture, this paper introduces...

BVI-SynTex was generated using a Computer Graphics Imagery (CGI) environment. It contains 186 sequences clustered in three different texture types. A subset of the BVI-SynTex dataset was selected to perform a subjective evaluation of compression using the MPEG HEVC codec (HM16.20).The publicly available BVI-SynTex dataset contains all source sequen...